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Multi-Party Controlled Semi-Quantum Dialogue Protocol Based on Hyperentangled Bell States.

Meng-Na Zhao1, Ri-Gui Zhou1, Yun-Hao Feng1

  • 1School of Information Engineering, Shanghai Maritime University, Shanghai 201306, China.

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Summary

This study introduces a secure multi-party controlled semi-quantum dialogue protocol using hyperentangled Bell states. It enhances security and efficiency for classical participants through distributed trust and Huffman compression.

Keywords:
Huffman compression codinghyperentangled bell statesmulti-party controlledsemi-quantum dialogue

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Area of Science:

  • Quantum Information Science
  • Computer Science

Background:

  • Semi-quantum dialogue systems face resource consumption and security vulnerabilities.
  • Single controlling parties are susceptible to information compromise.

Purpose of the Study:

  • To propose a multi-party controlled semi-quantum dialogue protocol addressing resource and security issues.
  • To enhance the security and efficiency of classical participants in quantum communication.

Main Methods:

  • Utilizes hyperentangled Bell states for the protocol.
  • Implements a multi-party controlled mechanism (Charlie1 to Charlie n) for distributed trust.
  • Integrates adaptive Huffman compression algorithm for classical participant data transmission.
  • Employs an "immediate measurement and transmission" mechanism.

Main Results:

  • The protocol establishes a distributed trust model, requiring collective authorization from all controllers.
  • Adaptive Huffman coding optimizes storage space complexity for classical participants.
  • Information-theoretic analysis proves the protocol's resistance to common attacks and malicious controllers.
  • Demonstrates high communication efficiency and lower resource consumption.

Conclusions:

  • The proposed protocol effectively solves resource consumption and security vulnerabilities in semi-quantum dialogue.
  • It offers robust security against untrustworthy controllers and collusion attacks.
  • The integration of Huffman compression enhances classical participant efficiency and data handling.